{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "faae5afa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 科学运算\n",
    "import pandas as pd \n",
    "import numpy as np \n",
    "# 绘图\n",
    "import matplotlib.pyplot as plt \n",
    "import seaborn as sns \n",
    "# 无视警告\n",
    "import warnings \n",
    "warnings.filterwarnings('ignore')\n",
    "# %matplotlib inline \n",
    "\n",
    "plt.rcParams['font.sans-serif'] = ['Microsoft YaHei'] #设置字体\n",
    "# sns.set(font='SimHei') #设置中文编码\n",
    "plt.rcParams['font.family'] = 'SimHei' #选择中文字体"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "10ef003b",
   "metadata": {},
   "outputs": [],
   "source": [
    "train_cleaned = pd.read_csv('B题-全部数据/order_train1.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7c5ab37a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import math\n",
    "\n",
    "# 绘制每个特征的分布  参数（数据集，列，宽，高，高距，宽距）\n",
    "def plot_distribution(dataset,cols=5,width=20,height=15,hspace=0.2,wspace=0.5):\n",
    "    plt.style.use('seaborn-whitegrid')  # 绘制风格 白网格\n",
    "    fig = plt.figure(figsize=(width,height))  # 画布大小\n",
    "    # 子图调整 上下左右都是None，就是设置图形的位置，边距\n",
    "    fig.subplots_adjust(left=None,bottom=None,right=None,top=None,wspace=wspace,hspace=hspace) #为了好看\n",
    "    #ceil：天花板。 取dataset的列，然后转换成float，除以我们的cols。 目的是求得我们要画多少行的图，例如求出来是3.5，我们就画4行\n",
    "    rows = math.ceil(float(dataset.shape[1]) / cols)\n",
    "    #以上都是准备工作\n",
    "    \n",
    "    for i,column in enumerate(dataset[code_col+num_col].columns):   # 遍历特征 （索引和列名） 每一列都是特征，所以我们遍历列就是遍历特征\n",
    "        ax = fig.add_subplot(rows,cols,i+1)  # 每遍历一下我们添加一个子图，我们子图占多少行多少列就已经确定了\n",
    "        ax.set_title(column)  # 设置标题\n",
    "\n",
    "        if column in code_col:  # 判断列的数据类型  object指的是非数据型特征\n",
    "            g = sns.countplot(y=column,data=dataset)  #画统计数量的条形图\n",
    "            plt.xticks(rotation=25)\n",
    "        else:\n",
    "            g = sns.distplot(dataset[column]) #绘制分布图\n",
    "            plt.xticks(rotation=25)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e33b528f",
   "metadata": {},
   "outputs": [],
   "source": [
    "code_col = ['sales_region_code','first_cate_code','second_cate_code','sales_chan_name']\n",
    "num_col = ['item_price','ord_qty']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "860c2884",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 2000x2000 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore') \n",
    "plot_distribution(train_cleaned,cols=2,width=20,height=20,hspace=0.45,wspace=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ecaa6c96",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
